What is the difference between the speed of Python and C++

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Introduction to DNA K-mers

DNA is a long-chain unit called nucleotides. There are four types of nucleotides in DNA, which are represented by the letters A, C, G and T respectively. Humans (or, more accurately, Homo sapiens) have 3 billion nucleotide pairs. For example, a small portion of human DNA might be similar to:

ACTAGGGATCATGAAGATAATGTTGGTGTTTGTATGGTTTTCAGACAATT

In this example, if any four consecutive nucleotides (that is, letters) are selected from the string, it will be a k-mer of length 4 (called 4-mer). Here are some 4-mers examples derived from this example: ACTA,CTAG,TAGG,AGGG,GGGA, etc.

Difficult and challenging

This article takes the generation of all possible 13-mers as an example, which is mathematically a permutation problem with substitution. Therefore, there are 4 (67108864) possible 13-mers. Here is a simple algorithm to generate the results in C++ and Python.

Scheme comparison

To make it easier to compare C++ and Python in this particular challenge, I used exactly the same algorithm in both languages. Both types of code are deliberately simple and similar in design. At the same time, avoid complex data structures or third-party packages or libraries. The first piece of code is written in Python.

Defconvert (c): if (c = ='A'): return'C' if (c = ='C'): return'G' if (c = ='G'): return'T' if (c = ='T'): return'A' print ("Start") opt = "ACGT" S = "" s_last = "" len_str = 13 for i inrange (len_str): s + = opt [0] for i inrange (len_str): s_last + = opt [- 1] pos = 0 counter = 1 while (s! = s_last) : counter + = 1 # You can uncomment the next line to see all k-mers. # print (s) change_next = True for i inrange (len_str): if (change_next): if (s [I] = = opt [- 1]): ss = s [: I] + convert (s [I]) + s [iTun1:] Change_next = True else: ss = s [: I] + convert (s [I]) + s [item1:] break # You canuncomment the next line to see all k-mers. # print (s) print ("Number ofgenerated k-mers: {}" .format (counter)) print ("Finish!")

It takes about 61.23 seconds to run the Python code and generate 67 million total 13-mers. To make a fair comparison, I commented out the line showing k-mers. You can also uncomment these two lines if you want to display them when you generate the k-mers. Note that it takes a long time to display all k-mers. If necessary, operate the CTRL+C abort code.

Now, take a look at the same algorithm in C++:

# include # include usingnamespacestd; charconvert (charc) {if (c ='A') return'C'; if (c = ='C') return'G'; if (c = ='G') return'T'; if (c = ='T') return'A'; return'' } intmain () {cout